100+ Exercises - Python Programming - Data Science - NumPy - Improve your Python programming and data science skills and solve over 100 exercises in NumPy!
- Created by Paweł Krakowiak
- English
What you'll learn
- solve over 100 exercises in NumPy
- deal with real programming problems in data science
- work with documentation and Stack Overflow
- guaranteed instructor support
Requirements
- completed course '200+ Exercises - Programming in Python - from A to Z'
- completed course '210+ Exercises - Python Standard Libraries - from A to Z'
- completed course '150+ Exercises - Object Oriented Programming in Python - OOP'
- basic knowledge of NumPy library
Description
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RECOMMENDED LEARNING PATH
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PYTHON DEVELOPER:
200+ Exercises - Programming in Python - from A to Z
210+ Exercises - Python Standard Libraries - from A to Z
150+ Exercises - Object Oriented Programming in Python - OOP
150+ Exercises - Data Structures in Python - Hands-On
100+ Exercises - Advanced Python Programming
100+ Exercises - Unit tests in Python - unittest framework
100+ Exercises - Python Programming - Data Science - NumPy
100+ Exercises - Python Programming - Data Science - Pandas
100+ Exercises - Python - Data Science - scikit-learn
250+ Exercises - Data Science Bootcamp in Python
SQL DEVELOPER:
SQL Bootcamp - Hands-On Exercises - SQLite - Part I
SQL Bootcamp - Hands-On Exercises - SQLite - Part II
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COURSE DESCRIPTION
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100+ Exercises - Python Programming - Data Science - NumPy
Welcome to the course 100+ Exercises - Python Programming - Data Science - NumPy, where you can test your Python programming skills in data science, specifically in NumPy.
Some topics you will find in the exercises:
working with numpy arrays
generating numpy arrays
generating numpy arrays with random values
iterating through arrays
dealing with missing values
working with matrices
reading/writing files
joining arrays
reshaping arrays
computing basic array statistics
sorting arrays
filtering arrays
image as an array
linear algebra
matrix multiplication
determinant of the matrix
eigenvalues and eignevectors
inverse matrix
shuffling arrays
working with polynomials
working with dates
working with strings in array
solving systems of equations
The course is designed for people who have basic knowledge in Python and NumPy package. It consists of 100 exercises with solutions.
This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.
If you're wondering if it's worth taking a step towards Python, don't hesitate any longer and take the challenge today.
Who this course is for:
- everyone who wants to learn by doing
- everyone who wants to improve their Python programming skills
- everyone who wants to improve their data science skills
- everyone who wants to prepare for an interview
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